Computational Design of Genetically Encodable Nanomachines

Alexis Courbet, researcher at University of Washington, described computational protein design and it’s emergent possibilities. A design pipeline is emerging where first a structure or combination of structures is proposed based off of a mechanical concept, then corresponding proteins are generated that match with each section of the structure. Alexis presented a large library of computationally designed protein rotors and motors, and hopes to use deep learning to improve on those designs and create more complex machines in the future.